Citations

Objective We investigated prolonged COVID-19 symptom duration, defined as lasting 28 days or longer, among people with systemic autoimmune rheumatic diseases (SARDs). Methods We analysed data from the COVID-19 Global Rheumatology Alliance Vaccine Survey (2 April 2021–15 October 2021) to identify people with SARDs reporting test-confirmed COVID-19. Participants reported COVID-19 severity and symptom duration, sociodemographics and clinical characteristics. We reported the proportion experiencing prolonged symptom duration and investigated associations with baseline characteristics using logistic regression. Results We identified 441 respondents with SARDs and COVID-19 (mean age 48.2 years, 83.7% female, 39.5% rheumatoid arthritis). The median COVID-19 symptom duration was 15 days (IQR 7, 25). Overall, 107 (24.2%) respondents had prolonged symptom duration (≥28 days); 42/429 (9.8%) reported symptoms lasting ≥90 days. Factors associated with higher odds of prolonged symptom duration included: hospitalisation for COVID-19 vs not hospitalised and mild acute symptoms (age-adjusted OR (aOR) 6.49, 95% CI 3.03 to 14.1), comorbidity count (aOR 1.11 per comorbidity, 95% CI 1.02 to 1.21) and osteoarthritis (aOR 2.11, 95% CI 1.01 to 4.27). COVID-19 onset in 2021 vs June 2020 or earlier was associated with lower odds of prolonged symptom duration (aOR 0.42, 95% CI 0.21 to 0.81). Conclusion Most people with SARDs had complete symptom resolution by day 15 after COVID-19 onset. However, about 1 in 4 experienced COVID-19 symptom duration 28 days or longer; 1 in 10 experienced symptoms 90 days or longer. Future studies are needed to investigate the possible relationships between immunomodulating medications, SARD type/flare, vaccine doses and novel viral variants with prolonged COVID-19 symptoms and other postacute sequelae of COVID-19 among people with SARDs.

A compact multi-energy soft x-ray diagnostic is being installed on the W Environment in Steady-state Tokamak (WEST), which was designed and built to test ITER-like tungsten plasma facing components in a long pulse (∼1000 s) scenario. The diagnostic consists of a pinhole camera fielded with the PILATUS3 photon-counting Si-based detector (≲100 kpixel). The detector has sensitivity in the range 1.6–30 keV and enables energy discrimination, providing a higher energy resolution than conventional systems with metal foils and diodes with adequate space and time resolution (≲1 cm and 2 ms). The lower-absorption cut-off energy is set independently on each one of the ∼100 kpixels, providing a unique opportunity to measure simultaneously the plasma emissivity in multiple energy ranges and deduce a variety of plasma parameters (e.g., Te, nZ, and ΔZeff). The energy dependence of each pixel is calibrated here over the range 3–22 keV. The detector is exposed to a variety of monochromatic sources—fluorescence emission from metallic targets—and for each pixel, the lower energy threshold is scanned to calibrate the energy dependence. The data are fit to a responsivity curve (“S-curve”) that determines the mapping between the possible detector settings and the energy response for each pixel. Here, the calibration is performed for three energy ranges: low (2.3–6 keV), medium (4.5–13.5 keV), and high (5.4–21 keV). We determine the achievable energy resolutions for the low, medium, and high energy ranges as 330 eV, 640 eV, and 950 eV, respectively. The main limitation for the energy resolution is found to be the finite width of the S-curve.

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

ABSTRACTBioinformatics approaches to examine gene‐gene models provide a means to discover interactions between multiple genes that underlie complex disease. Extensive computational demands and adjusting for multiple testing make uncovering genetic interactions a challenge. Here, we address these issues using our knowledge‐driven filtering method, Biofilter, to identify putative single nucleotide polymorphism (SNP) interaction models for cataract susceptibility, thereby reducing the number of models for analysis. Models were evaluated in 3,377 European Americans (1,185 controls, 2,192 cases) from the Marshfield Clinic, a study site of the Electronic Medical Records and Genomics (eMERGE) Network, using logistic regression. All statistically significant models from the Marshfield Clinic were then evaluated in an independent dataset of 4,311 individuals (742 controls, 3,569 cases), using independent samples from additional study sites in the eMERGE Network: Mayo Clinic, Group Health/University of Washington, Vanderbilt University Medical Center, and Geisinger Health System. Eighty‐three SNP‐SNP models replicated in the independent dataset at likelihood ratio test P < 0.05. Among the most significant replicating models was rs12597188 (intron of CDH1)–rs11564445 (intron of CTNNB1). These genes are known to be involved in processes that include: cell‐to‐cell adhesion signaling, cell‐cell junction organization, and cell‐cell communication. Further Biofilter analysis of all replicating models revealed a number of common functions among the genes harboring the 83 replicating SNP‐SNP models, which included signal transduction and PI3K‐Akt signaling pathway. These findings demonstrate the utility of Biofilter as a biology‐driven method, applicable for any genome‐wide association study dataset.

Restenosis after percutaneous transluminal coronary angioplasty is caused by neointimal hyperplasia, which involves impairment of nitric oxide (NO)-dependent pathways, and may be further exacerbated by a concomitant aging process. We compared the effects of NO-releasing-aspirin (NCX-4016) and aspirin (ASA) on experimental restenosis in both adult and elderly rats. Moreover, to ascertain the efficacy of NCX-4016 during vascular aging, we fully characterized the release of bioactive NO by the drug. Sprague–Dawley rats aged 6 and 24 months were treated with NO releasing-aspirin (55 mg/kg) or ASA (30 mg/kg) for 7 days before and 21 days after standard carotid balloon injury. Histological examination and immunohistochemical double-staining were used to evaluate restenosis. Plasma nitrite and nitrate and S -nitrosothiols were determined by a chemiluminescence-based assay. Electron spin resonance was used for determining nitrosylhemoglobin. Treatment of aged rats with NCX-4016 was associated with increased bioactive NO, compared with ASA. NO aspirin, but not ASA, reduced experimental restenosis in old rats, an effect associated with reduced vascular smooth muscle cell proliferation. NCX-4016, but not ASA, was well tolerated and virtually devoid of gastric damage in either adult or old rats. Thus, impairment of NO-dependent mechanisms may be involved in the development of restenosis in old rats. We suggest that an NCX-4016 derivative could be an effective drug in reducing restenosis, especially in the presence of aging and/or gastrointestinal damage.